AC-Band: A Combinatorial Bandit-Based Approach to Algorithm Configuration

December 01, 2022 ยท Declared Dead ยท ๐Ÿ› AAAI Conference on Artificial Intelligence

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Authors Jasmin Brandt, Elias Schede, Viktor Bengs, Bjรถrn Haddenhorst, Eyke Hรผllermeier, Kevin Tierney arXiv ID 2212.00333 Category cs.LG: Machine Learning Cross-listed cs.DS Citations 7 Venue AAAI Conference on Artificial Intelligence Last Checked 5 months ago
Abstract
We study the algorithm configuration (AC) problem, in which one seeks to find an optimal parameter configuration of a given target algorithm in an automated way. Recently, there has been significant progress in designing AC approaches that satisfy strong theoretical guarantees. However, a significant gap still remains between the practical performance of these approaches and state-of-the-art heuristic methods. To this end, we introduce AC-Band, a general approach for the AC problem based on multi-armed bandits that provides theoretical guarantees while exhibiting strong practical performance. We show that AC-Band requires significantly less computation time than other AC approaches providing theoretical guarantees while still yielding high-quality configurations.
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